Ayesa and Sener apply quantum computing to optimize hydrogen production

They leverage quantum algorithms to simulate the optimal operation of each process involved in an electrolysis plant.

The project is part of the digitalization objectives of the IPCEI (Important Project of Common European Interest) program led by Sener, aimed at improving electrolysis technologies and reducing the levelized cost of hydrogen. It will be presented at the 6th meeting of the Production vertical of the Basque Hydrogen Corridor (BH2C) on September 25.

Technology and engineering groups Ayesa and Sener have developed a proof of concept using a quantum solution to optimize operational simulations of electrolysis plants via the digital tool SenHy, developed by Sener. This solution enables the simulation of all processes involved in hydrogen production using quantum algorithms—from the management of various electricity sources (solar generators, power purchase from the grid, battery storage), through the operation and degradation management of electrolysis modules, to the adjustment of hydrogen output flow to align with demand forecasts.

The project aligns with the digitalization goals of the IPCEI program, focused on advancing electrolysis technologies and reducing the levelized cost of hydrogen (LCOH). As part of this effort, Sener has developed SenHy, an innovative operational simulation tool for electrolysis plants that integrates multiple electricity supply profiles into a single operational model. The project will be showcased at the 6th meeting of the Production vertical of the Basque Hydrogen Corridor (BH2C), to be held on September 25.

SenHy tackles a significant technical challenge: solving a complex multiphysics optimization problem every minute, based on the current and potential status of energy profiles and plant operation parameters. Given the limitations of traditional computing tools, simplifications had to be made to meet response time requirements. To accelerate this process and harness the full complexity of the multiphysics model, Sener conducted a proof of concept based on a quantum computing algorithm provided by Ayesa. The outcome was a success: a simplified problem was solved with the same solution quality in one-tenth of the time, opening the door to simulating more complex cases and significantly improving simulation accuracy.

This holistic vision, combined with the inherent scalability of quantum logic, allows for identifying optimal plant operating strategies in significantly reduced simulation times. This enables accurate planning over longer periods than what was previously possible with classical (non-quantum) methods.

Rapid resolution of complex problems

Electrolyzer plants are facilities that, by applying electric currents, can separate hydrogen and oxygen from water molecules. The hydrogen generated has multiple applications in industry and research and can also be used as a clean fuel.

It is a highly complex process which, until now, relied on classical methods when operational challenges arose—methods capable of delivering high-quality output within reasonable timeframes, but only for moderately complex problems. “As the complexity or scale of the problem increases, analysis times become prohibitive, and approximations or extrapolations must be used, resulting in outputs that are, at best, only indicative”, explains Iñigo Pérez Delgado, the project lead at Ayesa.

He further states, “We sought a scalable tool capable of delivering high-quality results with short execution times using a quantum method. We tested it within a range where classical methods can still verify result quality. The inclusion of a quantum algorithm enables the evaluation of scenarios with greater scale and complexity”.

Quantum logic allows an increase in problem complexity—which, in classical computing, leads to an exponential rise in difficulty—to be addressed with only a marginal increase in required processing power. “In this IPCEI project”, says Pérez Delgado, “the primary goal was to develop a method capable of delivering scalable results, even if no speed advantage was observed at the analyzed scale”.

“However”, he adds, “we’ve found that the problem analyzed, while moderate in size, is already large enough for the scalability of the quantum method to offer a speed advantage by an order of magnitude”. “Our results therefore confirm that quantum computing is now capable of delivering differential outcomes in the industrial sector”, he concludes.

According to Alfonso Corbella, R&D Project Director for Hydrogen at Sener, “The application of technologies such as quantum computing allows us to address the operational optimization of complex processes, such as those occurring in an electrolysis plant, with far greater precision. This advanced simulation capability not only improves efficiency but also paves the way for broader adoption of green hydrogen—a field in which Sener has extensive experience.”